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dc.contributor.authorLee, JCen_US
dc.contributor.authorChen, DTen_US
dc.contributor.authorHung, HNen_US
dc.contributor.authorChen, JJen_US
dc.date.accessioned2014-12-08T15:46:42Z-
dc.date.available2014-12-08T15:46:42Z-
dc.date.issued1999-04-15en_US
dc.identifier.issn0277-6715en_US
dc.identifier.urihttp://hdl.handle.net/11536/31400-
dc.identifier.urihttp://dx.doi.org/10.1002/(SICI)1097-0258(19990415)18:7<799en_US
dc.description.abstractDrug absorption in the human body depends on the dissolution rate of the drug. Suitable dissolution characteristics are important to ensure that the drug will achieve the desired therapeutic effects. To assess the similarity of dissolution rates of several drug lots, we apply a general growth curve model with different covariance structures. The Box-Cox power transformation and the naive log transformation are applied to a function of the dissolution rate. The predictive sample-reuse, or cross-validation, method is employed in selecting an appropriate model with best predictive accuracy. A testing procedure for examining the similarity among the drug lots is also conducted. A partially Bayesian approach is used for the assessment of dissolution equivalence. Copyright (C) 1999 John Wiley & Sons, Ltd.en_US
dc.language.isoen_USen_US
dc.titleAnalysis of drug dissolution dataen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/(SICI)1097-0258(19990415)18:7<799en_US
dc.identifier.journalSTATISTICS IN MEDICINEen_US
dc.citation.volume18en_US
dc.citation.issue7en_US
dc.citation.spage799en_US
dc.citation.epage814en_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.identifier.wosnumberWOS:000079580200004-
dc.citation.woscount8-
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